paper-with-me

Papers

Dis-moi comment tu varies ton d\'ebit, je te dirai qui tu es (Tell me how you vary your speech flow, I'll tell you who you are Studying inter-speaker variability makes it possible to identify discriminating or even identifying phonetic characteristics)

2020-06-01 · JEPTALNRECITAL 2020 6 · Estelle Chardenon, C{\'e}cile Fougeron, Nicolas Audibert, C{\'e}dric Gendrot

Si l{'}{\'e}tude de la variabilit{\'e} entre locuteurs permet d{'}identifier des caract{\'e}ristiques phon{\'e}tiques potentiellement discriminantes, voire sp{\'e}cifiques, il est essentiel de comprendre, si et comment, ces caract{\'e}ristiques varient chez un m{\^e}me locuteur. Ici, nous examinons la variabilit{\'e} de caract{\'e}ristiques li{\'e}es {\a} la gestion temporelle de la parole sur un nombre limit{\'e} de locuteurs, enregistr{\'e}s sur plusieurs r{\'e}p{\'e}titions dans une m{\^e}me session, et sur 6 {\a} 7 sessions espac{\'e}es d{'}une ann{\'e}e. Sur cette vingtaine d{'}enregistrements par locuteur, nous observons comment le d{\'e}bit articulatoire, les modulations de ce d{\'e}bit, et la dur{\'e}e des pauses varient en fonction de la r{\'e}p{\'e}tition et de la session et en interaction avec le locuteur. Les r{\'e}sultats montrent que c{'}est dans la variation de gestion temporelle de la parole que les locuteurs se distinguent les uns des autres, en termes de r{\'e}gularit{\'e} ou non entre enregistrements et au sein d{'}un m{\^e}me enregistrement.

📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Methods 이 논문이 사용한 방법론

UNS 설명 없음

Similar Papers 제목 키워드 기반

Posebits for Monocular Human Pose Estimation

2014-06-01 · CVPR 2014 6 · Gerard Pons-Moll, David J. Fleet, Bodo Rosenhahn

We advocate the inference of qualitative information about 3D human pose, called posebits, from images. Posebits represent boolean geometric relationships between body parts (e.g., left-leg in front of right-leg or h…

3D Pose EstimationImage RetrievalPose EstimationRetrieval

Automatic Article Commenting: the Task and Dataset

2018-05-09 · ACL 2018 7 · Lianhui Qin, Lemao Liu, Victoria Bi, Yan Wang 외

Comments of online articles provide extended views and improve user engagement. Automatically making comments thus become a valuable functionality for online forums, intelligent chatbots, etc. This paper proposes the new…

ArticlesComment Generation

PhoneBit: Efficient GPU-Accelerated Binary Neural Network Inference Engine for Mobile Phones

2019-12-05 · Gang Chen, Shengyu He, Haitao Meng, Kai Huang

Over the last years, a great success of deep neural networks (DNNs) has been witnessed in computer vision and other fields. However, performance and power constraints make it still challenging to deploy DNNs on mobile de…

GPU

Talking to the crowd: What do people react to in online discussions?

2015-07-08 · EMNLP 2015 9 · Aaron Jaech, Victoria Zayats, Hao Fang, Mari Ostendorf 외

This paper addresses the question of how language use affects community reaction to comments in online discussion forums, and the relative importance of the message vs. the messenger. A new comment ranking task is propos…

Not All Comments are Equal: Insights into Comment Moderation from a Topic-Aware Model

2021-09-21 · RANLP 2021 9 · Elaine Zosa, Ravi Shekhar, Mladen Karan, Matthew Purver

Moderation of reader comments is a significant problem for online news platforms. Here, we experiment with models for automatic moderation, using a dataset of comments from a popular Croatian newspaper. Our analysis show…

All